In the module 5 of intro to business analytics , data analytics and data science can you please provide me with more examples regarding the topics exclusively in data science and data analytics and also exclusively for data analytics .
Thanks for reaching out.
Hopefully, the following reply will explain the concepts further.
Data Analytics – think of it as combination of mathematical skills/quantitative methods and quantitative data, excluding any business concept. You don’t need to understand precisely what Digital signal processing is about; it is enough to remember it involves computations and predictions about future behaviour of signal, using the available quantitative data (which is, again, about the signal). There’s no business context here.
Data Science – it is analogous, however its applicability is not as general as the one of Data Analytics (as you pointed out). Thus, it concentrates on a smaller set of quantitative methods. Today, to this term, almost always a business connotation is attached. However, since it is almost always, here’s an exception: Optimization of drilling operations. In this discipline, the quantitative methods for Data Science, as opposed to Data Analytics have been used (yes, the same methods can be considered to be part of Data Analytics, but they are referred to as Data Science today. We could only wish every method could fall in its own category in our diagram, but this is not the case. So, we prefer exposing the truth by categorizing the way these terms are used today rather than re-organizing everything).
Finally, to the left of Optimization of drilling operations, you could see Data Science tools/methods applied within the context of business.
At this point, I wouldn’t worry more about these distinctions. I am sure that as you proceed with the course, many things will become clearer.
Hope this helps.
so basically what was earlier called as data analytics simply can come under data science today ?
Not exactly. Part of what used to be called ‘data mining’ is called ‘data science’ today. Rather, you can say that ‘data science’ involves many ‘data analytics’ tools, while adding business context to them.